{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.1.2'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras import datasets, layers, models\n",
    "\n",
    "import os\n",
    "import time\n",
    "import json\n",
    "import glob\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from PIL import Image\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "import seaborn as sns\n",
    "\n",
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "model_path = './saved_model/alexnet-4char-with-upper-letters'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "input_1 (InputLayer)         [(None, 100, 120, 3)]     0         \n",
      "_________________________________________________________________\n",
      "conv2d (Conv2D)              (None, 98, 118, 32)       896       \n",
      "_________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D) (None, 49, 59, 32)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_1 (Conv2D)            (None, 47, 57, 64)        18496     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 23, 28, 64)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 21, 26, 64)        36928     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_2 (MaxPooling2 (None, 10, 13, 64)        0         \n",
      "_________________________________________________________________\n",
      "flatten (Flatten)            (None, 8320)              0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 1024)              8520704   \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1024)              1049600   \n",
      "_________________________________________________________________\n",
      "reshape (Reshape)            (None, 4, 256)            0         \n",
      "=================================================================\n",
      "Total params: 9,626,624\n",
      "Trainable params: 9,626,624\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = tf.keras.models.load_model(model_path)\n",
    "\n",
    "# Check its architecture\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_y(y):\n",
    "    return ''.join(map(lambda x: chr(int(x)), y))\n",
    "\n",
    "def predict(image_path):\n",
    "    im = Image.open(image_path)\n",
    "    # im = im.resize((H, W))\n",
    "    im = np.array(im) / 255.0\n",
    "    im = np.array(im)\n",
    "    \n",
    "    y_pred = model.predict(np.array([im]))\n",
    "    y_pred = tf.math.argmax(y_pred, axis=-1)\n",
    "    \n",
    "    print('predict: %s' % format_y(y_pred[0]))\n",
    "    plt.imshow(im)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predict: KJWE\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "predict('./images/char-4-epoch-1/train/KJWE_a759b2b4-d34a-47b7-908e-9d6346824db9.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
